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FACTORS INFLUENCING
INDONESIAN MILLENIALS’ TRAVEL DECISION:
A CASE OF BANGKOK
Farida Komalasari1 and Eko Ganiarto2 farida_k@president.ac.id1, eganiarto@gmail.com2
1Business Administration Study Program, Faculty of Business, President University
2Management Study Program, Faculty of Business, President University Abstract
The number of Indonesian millenials visiting Bangkok is increase year by year.
There must be a strong reason, why Indonesian millenials decide to visit Bangkok.
This research aims to find out the factors influencing Indonesian millenials’ travel decision to visit Bangkok. The push and pull travel motivations theory are used to develop the research framework. A quantitative research with primary data collected by using a questionnaire is done. The data analysis used in this research is linear regression. There are two models, multiple linear regression and simple linear regression. A multiple linear regression is used to find out the factors of traveler satisfaction, while a simple linear regression is used to find out the influence of traveler satisfaction toward travel decision. The result shows that there are five push factors and five pull factors influencing traveler satisfaction, and at the end, traveler satisfaction influences travel decision. The five push factor are knowledge and culture, friendship, social status, sightseeing, and new experience. Meanwhile the five pull factors are local values, destinations features, historical values, cultural values, and outdoor attraction. Relaxation, as a part of push factor, does not influence traveler satisfaction.
Keywords: Push and Pull Travel Motivations, Traveler Satisfaction, Travel Decision, Indonesian Millenial, Bangkok
A. INTRODUCTION
Thailand is acountry that is successful in attracting foreign tourists. This success made the tourism industry become one of the mainstays in the Thailand economy. World Travel and Tourism Councilreported that the total contribution of Travel and Tourism sector to Thailand’s GDP was 21.2% in 2017, and it projected to rise become 28.2% in 2028 (Bangkok Bank, 2019).
Based on data from the Mastercard Global Destination Cities Index, Bangkok - the capital city of Thailand - has been designated as the city with the most tourist arrivals in the world in the last three years, 2016 (21.5 million tourists), 2017 (20.5 million tourists) and 2018 (21.98 million tourists).Figure 1 shows that the number of foreign tourist visits to Thailand also tends to increase from year to year, especially since 2010, except in 2014 which declined due to the political crisis (Robino, 2019).
In line with the increasing number of foreign tourists to Bangkok, the number of tourists from Indonesia to Bangkok also shows the same trend.
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Tourism industry playersin Indonesia predict that the number of outbound tourists of Indonesiawill increase 8.6% from 2016 to 2021 (Andriani, 2018).
The success of Thailand in attracting foreign tourists is an interesting phenomenon, especially when compared to Indonesia. In 2017, there were 575,000 Indonesian tourists visiting Thailand. While Thailand tourists visiting Indonesia only amounted to 138,235 people or less than a quarter (thaiwebsites.com, 2020). In fact, tourist destinations and tourist attractions in Indonesia are not inferior to Thailand (Bangkok) and even more interesting and varied. This condition raises some questions, like why the tourist prefer go to Thailand than the neighbours (Malaysia, Vietnam or Indonesia)? W hat factors that make Bangkok (Thailand) more attractive to be visited by foreign tourists including the Indonesian millennials?How attractive the tourism destination in Thailand? That is why this research is conducted to answer the questions.
Figure 1
Yearly Tourist Arrivals in Thailand, 2003 – 2018 (in million tourists)
Source: thaiwebsites.com, 2020
Based on the above explanation, there are some problems to be answered. Why are so many foreign tourists visiting Thailand (Bangkok), including Indonesian millennials? What tourist destinations are interesting to be visited?What are the push and pull factors impacting travelers’ satisfaction in visitng Bangkok? Is there any influence of travelers’ satisfaction toward tourist travel decision? Therefore, a study about the factors influencing Indonesian millenials travel decision to Bangkok is really important to answer those questions. So, the aims of this research are:
1. To determine the favourite destination in Bangkok
2. To know the travelers’ satisfaction to Bangkok and its factors 3. To know the influence of travelers’ saticfaction toward tourist travel
decision to Bangkok B. LITERATURE REVIEW
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Tourist Travel Decision
Tourist travel decision is a process of decision making in visiting of tourist destinations. Tourist travel decision is affected by internal factors and external factors(Ni, Tsao, Wang, 2017). As introduced by Dann (1977, cited by Komalasari & Zharfan (2017)), these factors are well known as travel motivation, and classified by push factors and pull factors. Push factors are the internal factors, and pull factors are the external factors. These factors will be explained more detail on the next part. The decision to revisit/return to the previous destination are influenced by destination satisfaction (Khuong &
Ha (2014), Putra (2016), Komalasari & Ganiarto (2018)).
Tourist Destination Satisfaction
Tourist destination satisfaction or traveler satisfaction is defined as the overall enjoyment felt as the result of the tour experiences and could be teh result of the comparison between the tourist’s expectation before visiting, as part of the pre–visitation activity, with theexperience during visitation, as part of during-visitation activity (summarized from Chen & Tsai (2007), McDowall (2010), Osman (2013), Ngoc & Trinh (2015)). Some factors influence traveler satisfaction, such astravelers’ needs, wants and desires (Osman, 2013), natural and cultural environment (Ngoc & Trinh, 2015), and tourist motivation (Prebensen, Skallerud& Chen , 2010). Meanwhile, a study conducted by Komalasari & Ganiarto (2018) in Labuan Bajo found that the pull factors, such as historical value, local value, culture and heritage, and travelling value, affect tourist satisfaction significantly.
The Tourist Motivation
Based on Dann (1977) (cited by Komalasari & Zharfan, 2017), tourist motivation could be devided into two categories. Those are push factors as an internal factors and pull factors as an external factors. Including in the push factors are internal motivation, such as personality, self-esteem, attitudes, rest and relax, escape, prestige, perceptions, interests, and others;
socio economic and demografic factors, such as education, gender, disposable income, etc; and knowledge and experience. Including in the pull factors are destination attributes, suh as climate, history sights, culture, language, scenic beauty, snow, etc.; accessibility, such as toll-road, transportation, etc; maintenance/sutiational factors, such as safety, security, seasonality, etc.; market image, such as negative/positive images, quality of services, facilities, visa entry condition, etc; other people, such as family, peers, travel companions (summarized from Komalasari & Zharfan, 2017; Ni, et al., 2017).
C. Research Method
Theoretical Framework and Hypothesis
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According to the research objectives and the literature review,this researchuses three blocks of variable. The push and pull factors of tourist motivation is the first block and treated as independent variable. Traveler satisfaction is the second block and treated as dependent variable of tourist motivation, and as independent variable for travel decision. Travel decisionis the third block and treated as dependent variable of traveler satisfaction. The relationship of them is figured out on Figure 2, a Theoretical Framework, which consists of 2 models.
Figure 2
Theoretical Framework The First Model:
The Second Model:
According to the theoretical framework above, the hypothesis from the first model is H1: push factors influence traveler satisfaction and H2: pull factors influence traveler satisfaction. Meanwhile, the hypothesis from the second model is H3: traveler satisfaction influences travel decision.
Variable Measurement and Research Instrument
The all variables are measured by construct statements, which are measured by using 5 (five) likert scale. All the contructstatements are organized in a set of questionnaire. The questionnaire is not only to measure the variable, but also to get other data needed to support this research.
Completely, the questionnaire consists of 5 (five) parts; those are screening question, respondent profile, trip for leisure profile, favourite destination, and construct statements.
The screening question is used to make sure that the respondents are Indonesian millenials and experiencing Bangkok as their travel destination.
The respondent profile is used to figure out the respondents based on their gender, age, education, occupation, income, and marital status. The trip for
Push Factors Pull Factors
Traveler Satisfaction
Travel Decision Traveler
Satisfaction
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leisure profile consists of the frequency of visiting Bangkok, the travel companion, and average spending for one Bangkok trip. The favourite destination part is used to figure out the main favourite destination visited by Indonesian millenials.
The last part is the main part of the questionnaire, that is variable mesurements. The first variable is push factors, consists of 21 internal factors. The second variable is pull factots, consists of 22 external factors.
The third is traveler satisfaction, consists of 17 destination’s features. The last variable is travel decision, consists of 8 construct measurements. The questionnaire is modified from Kesterson (2013).
Data Collection MethodandSampling Design
This research uses primary data, collecteddirectlyusing printed questionnaire, from Indonesian millenials experiencing Bangkok. The content validity and reliability test is applied to test the validity and reliability of the construct statements.
The population are Indonesian millennialswho have experience visiting Bangkok.The sample size is 277, selected by using non-probability sampling, which is convenience sampling.
Data Analysis Method
The procedure of data analysis is started from data tabulationand ended with hypothesis testing. Below is the detail step of the data analysis:
1. Validity and reliability test
To test the construct validity, this research uses the Kaiser-Meyer-Olkin (KMO) and Bartlett’s Test. The construct satement is considered to be valid if the KMO Measure of Sampling Adequacy (KMO-MSA) is >= 0.5 and the Bartlett’s Test of Sphericity is =< 0.05 (Stephanie, 2020).
To test the construct reliability, this research uses the Cronbach’s Coefficient Alpha. The construct statement is considered to be reliable if the Cronbach’sAlphaValue is greater than 0.5(Mostafavi, Keshavarz
& Mohammadi, 2016).
2. Factoring analysis
Factoring analysis is used to construct a new variable from 21 construct statements of push factors and 22 construct statements of pull factors. The new variable could be formed based on the each column, whhich is shown on the table of the rotated component matrix value.
3. Inferential analysis
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Based on the theoretical framework, there is two model in this research. The first model will be analyzed by using multiple linear regression, and the secodn by using simple linear regression. The step of each analysis is below:
a. A classical assumption test
This test is done to make sure that the data used are fulfill the requirements to be analyzed using linear regression. The test includes normality, homoscedasticity, and multicolinearity (Chatterjee & Simonoff, 2013).
b. The goodness of fit test
This test is done to make sure that the observe data correspond to the fitted (assumed model). The model is considered to be fit if the p-value of the F-test is less than or equal 0.05 (PennState Eberly College of Science, 2020).
c. Coefficient determination analysis
This analysis is well known as R-square analysis, which expected value is bigger than 0.7; meaning that the independent variable(s) significantly determines the variability of the dependent variable (Ogee, Ellis, Scibilia, Pammer, & Steele, 2014).
d. Hypothesis testing
In this research, the hypothesis testing is done with the the confidence level 95%. So, the criteria to accept the hypothesis when the CR is >= 1.96 and the p-value is =< 0.05 (Hair, Black, Babin, & Anderson (2010).
D. Result and Discussion Respondent Profile
Figure3 shows the respondents’ profile.The total respondent in this research are 277 respondents, that consist of 125 male (45%) and 152 female (55%). Based on their highest education, 61% of them are undergraduate program. About the respondens’ occupation, more than half of them (77%) are students. Lastly is about thieir marital status, which is 90% are single.
Figure 3 also shows that most of the respondents visit to Bangkok as their first visit (57%). To travel to Bangkok, most of respondents spend around IDR2,500,000 – IDR7,500,000/trip/person.
Figure 4 shows the respondents’ income. Around half of them are persons with income less than Rp 5,000,000 (54%).
Figure 3
The Respondent’s Profile
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Figure 4
Respondent by Income
Validity and Reliability
There are 21 construct statements of push factors and 22 construct statements of pull factors. These all must be tested the validity and the reliability. The test result on Table 1 and Table 2 showthat the KMO-MSA
Femal…
Male 45%
(1) Respondents by Gender
, 0, 0%
Senior …
Under-…
Post-…(2) Respondents by Education
Student Em-ployee
Business Owner
(3) Respondents by Occupation
Single 90%
Married/living together
9%
Widowed 1%
(4) Respondents by Marital Status
1 time 2 times
27%
3 times
4 times 5 times and more
(5) Frequency to Bangkok
< 2,500,000 4%
2,500,000 - 4,999,999
39%
5,000,000 - 7,499,999
34%
7,500,000 - 9,999,999
12%
10,000,000 - more 11%
(6) Respondents by Spending/trip/person
0%
< 5,000,000 54%
5,000,000 - 9,999,999 30%
10,000,000 -…
15,000,000 -…
20,000,000 - 24,999,999…
Profesional
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values for the push and pull factors are 0.777 and 0.830; higher than the cut–
off value (0.5). The significance value of Bartlett’s Test of Sphericity is 0.000 for both push and pull factors’; below than the cutt-off value (0.05). So, it can be concluded that the all construct statements are valid.
Meanwhile, the value of the Cronbach’s Alpha is 0.938, higher than 0.6 as the cut-off value. So, it can be said that the all construct satements are reliable.
Tabel 1
KMO and Bartlett’s Test of Push Factors Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
,777 Bartlett's Test of
Sphericity
Approx. Chi-Square 1469,96 5
Df 210
Sig. ,000
Tabel 2
KMO and Bartlett’s Test of Pull Factors Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
,830 Bartlett's Test of
Sphericity
Approx. Chi-Square 1937,76 9
df 231
Sig. ,000
Factoring Analysis
Based on the result of factoring process, that can be seen on the table of the rotated component matrix value, there are sixnew variables formed from 21 push factors’ construct statements and five new variables formed from 22 pull factors’ construct statements. Below is the new variables.
1. Push Factors:
a. Knowledge and Culture; this variable comes from the statements/questions about:
i. enhancing communication with local community ii. enhancing or improve knowledge
iii. exchanging customs and traditions
iv. experiencing new and different life styles or traditions v. exploring cultural resources
vi. meeting new people
b. Friendship; this variable comes from the statements/questions about:
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i. This factor comes from the questions about:
ii. away from home
iii. visiting a destination that would impress my friends and family iv. visiting a place friends have not been to
v. visiting a place that friends have been to
c. Social status; this variable comes from the statements/questions about:
i. increasing social status ii. learning about the past iii. visiting friends and relatives
d. Sightseeing; this variable comes from the statements/questions about:
i. sightseeing scenic attractions ii. sightseeing touristic spots
e. Relaxation; this variable comes from the statements/questions about:
i. participating in new activities ii. relaxing physically
iii. satisfy the desire to be
f. New experience; this variable comes from the statements/questions about:
i. having an enjoyable time with travel companion(s) ii. seeking novelty
iii. visiting a place you have not visited before 2. Pull Factors:
a. Local value; this variable comes from the statements/questions about:
i. reliable weather/climate
ii. safe destination/Personal safety iii. souvenirs
iv. standards of hygiene and cleanliness v. traveling to a local or nearby destination vi. traveling to place people appreciate vii. warm welcome for tourists
b. Destination features; this variable comes from the statements/questions about:
i. activities for entire family ii. affordable tourist destination iii. availability of pre-trip tourist info iv. interesting culinary
v. value for money vi. variety of short tours
c. Historical value; this variable comes from the statements/questions about:
i. heritage sites ii. historical locations iii. historical reenachment iv. history
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d. Culture value; this variable comes from the statements/questions about:
i. culture, arts, and traditions ii. festivals and events
iii. good transportation mode
e. Outdoor attraction; this variable comes from the statements/questions about:
i. outdoor activities
ii. outstanding scenic attraction
The next step is processing the inferential analysis by using six new variables of push factors and five new variables of pull factors.
Inferential Analysis
Based on the factoring analysis result, now there are six push factor variables (knowledge and culture, friendship, social status, sightseeing, relaxation, and new experience) and five pull factor variables (local values, destination features, historical value, culturalvalues and outdoor attraction).
The next is the inferential analysis by using two models. The first model is multiple linear regression model, to examine the influence of 11 variables of push and pull factors toward traveler satisfaction in visiting Bangkok. The second model is simple linear regression model, to examine the influence of traveler satisfaction toward travel decision. Below is the explanation of each model, consists of the classical assumption test, the goodness of fit test, coefficient determination analysis, and hypothesis testing
1. Multiple linear regression (Model 1)
This model includes 11new push and pull variafactors as independent variables and traveler satisfaction as dependent variable. Then the new hypotheses can be formulated as follows:
H1. Knowledge and culture influences the traveler satisfaction H2. Friendship influences the traveler satisfaction
H3. Social status influences the traveler satisfaction H4. Sightseeing influences the traveler satisfaction H5. Relaxation influences the traveler satisfaction H6. New experience influences the traveler satisfaction H7. Local values influences the traveler satisfaction
H8. Destination features influences the traveler satisfaction H9. Historical values influences the traveler satisfaction H10. Cultural values influences the traveler satisfaction H11. Outdoor attractions influences the traveler satisfaction
H12. The eleven independent variables jointly influence the traveler satisfaction
The classical assumption test for this multiple regression model includes normality, homoscedasticity and multocolinearity. The normal
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distributed data are required in the analysis using Multiple Regression. The result of data processing shows that the data meet the requirement (Figure 5), spread out near the diagonal line and form a linear pattern. It means the data are normally distributed.
Figure5
Normal P-P Plot of Regression Standardized Residual, Multiple Regression (Model 1)
The result of the homoscedasticity test can be seen in Figure 6. The scatter plot shows that the dispersion of the data does not form a specific pattern. It means that its variance is constant (homoscedastic) and meets the requirement.
Figure6
Scatterplot, Multiple Linear Regression (Model 1)
Table 3 shows the value of VIF for every variable is less than 10. It means there is no multicolinearity between the variables. Beside that, the value of Tolerance also is higher than 0.5 and approach to 1. It indicates there
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is no colinearity between independent variables. Both VIF and Tolerance values indicate that there is no multicolinearity in this regression analysis and it meets the requirement.
Table 3
Multicolinearity Test Result
No. Variable
Collinearity Statistics Tolerance VIF 1 Knowledge &
Culture
,752 1,331
2 Friendship ,862 1,160
3 Social Status ,850 1,176 4 Sightseeing ,943 1,061 5 Relaxations ,750 1,332 6 New Experience ,772 1,296 7 Local Value ,744 1,345 8 Destination
Features
,693 1,444 9 Historical Value ,904 1,106 10 Culture Value ,726 1,377 11 Outdoor
Attraction
,921 1,086
The next is the goodness of fit test. Tabel 4shows that the value of significance-F (sig) is 0.000 or below 0.05 (significance level). It means that the model is good-fit, and H12 is accepted. Meaning that the 11 push and pull factors could explain the variability of traveler satisfaction. In other word it can be said that the eleven variables jointly significantly influence traveler satisfaction.
Table 4
ANOVA (Analysis of Variance), Model 1
Model
Sum of
Squares Df Mean Square F Sig.
1 Regression 40,785 11 3,708 33,958 ,000b
Residual 28,825 264 ,109
Total 69,609 275
Table 5shows the value of adjusted R2, that is 0.569. It means 56.9%
variation of traveler satisfaction can be explain by the changes of the all 11 independent variables (knowledge and culture, friendship, socialstatus, sightseeing, relaxation, new experience, localvalues, destinationfeatures,
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historicalvalues, culturalvalues,and outdoor attraction). The remaining can be explained by other variable(s) that not included in the analysis.
Table 5
Model Summaryb, Model 1 Model R R Square
Adjusted R Square
Std. Error of the Estimate
1 ,765a ,586 ,569 ,33043
a. Predictors: (Constant), Outdoor Attraction, Cultural Value, Historical Value, Destination Features, local Value,
Sightseeing, Friendship, Social Status, New Experience, Knowledge and Culture, Relaxation
b. Dependent Variable: Satisfaction
The last part is the hypothesis testing or well known as t-Test. This is used to examine whether the independent variable partially influence the dependent variable or not by seeing the value of sig. (significance) in coefficient table. If the value of sig. is less than 0.05 it means that the independent variable significanly influence the dependent variable. Otherwise, if the significance value is more than 0.05, it means the independent variable does not influence the dependent variable.
Table 6 shows that the significance values (sig.) of almost all variables are below than 0.05 (significance level), except relaxation. It means, from six push factors (variables), there are five factors (variables) – (knowledge and culture, friendship, social status, sightseeing, and new experience)–
significantly influence traveler satisfaction. Meanwhile, relaxation does not, since the value of significance is 0.474 (more than 0.05). For the pull factors (variables), all pull factors – local value, destination features, historical value, cultural value and outdoor attraction – significantly influence traveler satisfaction. It can be seen from the value of significance is lower than 0.05 (see Table 6).
Table 6
Coefficients of Regression Analysis, Model 1
Model Unstandardized
Coefficients
Standardiz ed Coefficient
s t Sig. Collinearity
Statistics Beta
Std.
Error Beta TOL VIF
(Constant) 3,693 ,020 185,680 ,000
Knowledge and Culture
,096 ,023 ,191 4,182 ,000 ,752 1,331
Friendship ,109 ,021 ,218 5,100 ,000 ,862 1,160
Social Status ,086 ,022 ,172 4,000 ,000 ,850 1,176
Sightseeing ,043 ,021 ,086 2,108 ,036 ,943 1,061
Relaxation ,016 ,023 ,032 ,711 ,478 ,750 1,332
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New Experience ,049 ,023 ,098 2,174 ,031 ,772 1,296
Local Value ,160 ,023 ,317 6,905 ,000 ,744 1,345
Destination Features
,064 ,024 ,126 2,658 ,008 ,693 1,444 Historical Value ,093 ,021 ,185 4,442 ,000 ,904 1,106
Cultural Value ,111 ,023 ,220 4,744 ,000 ,726 1,377
Outdoor Attraction ,104 ,021 ,206 4,984 ,000 ,921 1,086 a. Dependent Variable: Satisfaction
2. Simple linear regression (Model 2)
The second model is used to check the influence of traveler satisfation toward travel decision. So, traveler satisfaction is treated as independent variable and travel decision as dependent variable. A simple linear regression is used, with the hypothesis as follows:
H13. Traveler satisfaction influences travel decision
Below is the result of the classical assumption test for simple regression analysis, that consists of normality test and homoschedasticity test. There is no multicolinearity test because this model has only one independent variable.
Figure 7shows that the data points spread out near the diagonal line and form a linear pattern. It means the data is normally distributed.
Figure7
Normal P-P Plot of Regression Standardized Residual, Simple Regression (Model 2)
The result of the homoscedasticity test can be seen in Figure 8, shows that the dispersion of the data does not form a specific pattern. It means that its variance is constant (homoscedastic) and meets the requirement.
Figure8
Scatterplot, Linear Regression (Model 2)
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Table 7 shows the result of the goodness of fit for the simple linear regression. The value of significance F (Sig.F) is 0.000 or below 0.05 (significance level). It means the second model is fit. So it can be said that the variability of travel decision is determined by traveler satisfaction. How big? It can be seen on Table 8. The value of adjusted R2 is 0.311, meaning that 31.1% of travel decision can be explain by the changes of traveler satisfaction. The remaining (68.9%) can be explained by other factors (variables) that not included in the analysis.
Table 7
ANOVA (Analysis of Variance), Model 2
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 29,060 1 29,060 125,711 ,000b
Residual 63,570 275 ,231
Total 92,630 276
a. Dependent Variable: Travel Decision b. Predictors: (Constant), Satisfaction
Table 8
Model Summaryb, Model 2 R R Square
Adjusted R Square
Std. Error of the Estimate
,560a ,314 ,311 ,481
a. Predictors: (Constant), Satisfaction b. Dependent Variable: Travel Decision
The last part is the hypthesis testing for the second model. Table 9 shows the the t-test result. The significance value (sig.) is below that 0.05 (significance level). It means H13 is accepted. Meaning the traveler satisfaction significantly influencestravel decision.
Table 9
Coefficients of Regression Analysis, Model 2
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Unstandardized Coefficients
Standardize d Coefficients
t Sig.
Collinearity Statistics B Std. Error Beta
Toleranc
e VIF
1 (Constant) 1,633 ,215 7,604 ,000
Satisfaction ,646 ,058 ,560 11,212 ,000 1,000 1,000 a. Dependent Variable: Travel Decision
Discussion
The inferential analysis result shows that five out of six push factor variables influence the Indonesian millenials’ satisfaction in visiting Bangkok. Those are knowledge and culture, friendship, social status, sightseeing, and new experience. Another variable, relaxation does not influence their satisfaction.
The inferential analysis result also shows that all five pull factor variables influence the Indonesian millenials’ satisfaction in visiting Bangkok. Those are local values, destination features, historical values, cultural values, and outdoor attractions.
Figure 9 shows their six favourite destinations. Chatucak Market is an indoor and outdoor market, opened in the weekend, using traditional market concept, providing anything and everything such as fashion, global and local food, handycraft, and jewelery. Street food stalls is the one of the main destination in Bangkok. At least there are 13 best spots for street food in Bangkok (Plumridge, 2019). People could be enjoying hundreds varian of local foods. Usually the street food stalls are located along the street in front of shopping center. So, the Indonesian millenials can do shopping and enjoying the local food. Terminal 21 is a world cities-themed shopping mall, with unique concept that places several world-famous cities and its landmark under one roof. Global and local fashion brand, global and local cullinary are provided in this mall. Wat Pho and Wat Arun are Buddhist temple, located in the heart of Bangkok City. Wat Pho and Wat Arun are two of the Bangkok’s oldest temple, and recognized by UNESCO (thaiwebsites.com, 2020). These two temples have a long history since these are built in seventh century.
Khao San Road is well known as a backpacker centre.
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Using destination classification concepts, introduced by Kusen & Tomljenovic (2002), those six destinations could be classified into two groups. Chatucak Market, Terminal 21, Food Stalls Streets, and Khao San Road are lifestyle destinations, meanwhile Wat Pho and Wat Arun are protected cultural heritage destinations.
From push factor side, the lifestyles destinations fulfill the needs of Indonesian millenials to get friendship, social status, sightseeing, and experince. Shopping and enjoying cullinary are the activities that usually done by the young generation to increase their friendship. They prefer to go shoopping and enjoying cullinary with friends. They can post the shopping and enjoying cullinary pictures on social media, since 56% of the Indonesia’s population are social media users and mostly they are in the range of age 18- 34 years, which are millenials (wearesocial.com, 2019). Posting the pictures is their way to increase the social status. More frequently, travelers visiting lifestyle destination just for enjoying the atmosphere and getting new experience, with no or less transaction. It can be seen from the income data, show that 54% of them are traveler with income less thad IDR 5,000,000 (Figure 4). Meanwhile, the protected cultural heritage destinations, Wat Pho and Wat Arun, fulfill the two push factors, knowledge and culture and sightseeing. Many knowledge and culture could be taken from these two destinations. The Indonesian millenials also enjoy the two temple structure and landscape. These fulfill their sightseeing motivation. Observing the temple structure and the detail of the temple wall give them a new sensation in traveling. As much as 69% feel satisfied with the history/culture and 59%
satisfied with the landscape (Figure 10).
From pull factor side, lyfestyle destinations fulfill the needs of Indonesian millenials to get local values, destination features, and outdoors attraction.
The Indonesian millenials are very satisfied with the local food at those four lyfestyle destinations, Chatucak Market, Terminal 21, Street Food Stalls and Kha San Road (Figure 10). Meanwhile, the protected cultural heritage destinations, Wat Pho and Wat Arun, fullfill Indonesian millenials’ needs
62%
62%
70%
71%
76%
79%
0% 20% 40% 60% 80% 100%
Khao San Road Wat Arum Wat Pho Terminal 21 Street Food Stalls Chatucak Market
Figure 9
Favourite Destination Destination
Percentages of Respondent Most Likely to Visit
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toward historical values and cultural values. From these two destinations, traveler get more information about the history of Thailand and Bangkok as a capital city and its culture. There are many guide, who are ready to explain about the Thailand and Bangkok history and culture. The information also could be taken from leaflet and information board that are avaalable in every destination. As much as 72% travelers are satisfied toward tourist information (Figure 10).
Figure 10 shows that the highest satisfaction of respondent is in cuisine/cullinary (78%), followed by entertainment (77%), and tourist information (72%). Figure 11 shows the Indonesian millenials destination’s worthiness of Bangkok. They are gaining new knowledge and experiences and good value of money. There are 75.5% respondents gaining new knowledge and experiences, while80.9% respondents feel that Bangkok gives a good value of money.
49%
50%
51%
55%
57%
59%
60%
61%
61%
62%
65%
67%
69%
72%
72%
77%
78%
0% 20% 40% 60% 80% 100%
Language and communication Greenery Quiet/serenity Traffic Sea transportation mode Lanscape Land transportation mode Train transportation mode Hospitality and assitance Safety Tidiness of public area Restaurant quality History/culture Hotel quality Tourist information Entertainment Cuisine/cullinary
Figure 10
Satisfied Respondent by the Source of Satisfaction Sources of Satisfaction
Percentages of Satisfied Respondent
75.5% 80.9%
0.0%
50.0%
100.0%
Gain New Knowledge
and Experiences Good Value of Money Figure 11.
The Destinations' Worthiness of Bangkok Responden
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E. Conclusion and Recommendation
Based on the research objective and research result, it can be drawn some conclusions, as follow:
1. There are six favourite tourist destinations in Bangkok. They are Chatucak Market, Street Food Stall, Terminal 21, Wat Pho, Wat Arun and Khao San Road.
2. On average, 63% respondents are satisfied visiting to Bangkok. There are 78% respondents are satisfied with the cuisine/cullinary, followed by entertainment (77%), tourist information (72%), hotel quality (72%) and history/culture (69%).
3. There are push and pull factors that influence the Indonesian millenials satisfaction in visitingBangkok. The push factors are of knowledge and culture, friendship, social status, sightseeing, andexperience. Meanwhile, the pull factors are local value, destination features, historical value, cultural value and outdoor attraction.
4. Relaxation, as part of push factor, does not influence traveler satisfaction.
5. Traveler satisfaction significantly influencestravel decision to visit Bangkok.
6. Since there are many interesting place/moment in Bangkok, then there are almost 80percent respondents who recommend others to visit Bangkok.
Since the push and pull factors are significantly influence travelers’
satisfaction, formulating some strategies to get more traveler/tourist to Bangkok is really needed. The lifestyle destination and protected heritage culture destination are Indonesian millenials’ most favourite destinations.
Therefore, including those two types of tourist destinations into the tour package is a good decision for travel agent with Indonesian millenials as its customer segment. Beside those four lifestyle destinations that already mentioned in the previuos part, there are many others such as ICONSIAM and ICONLUXE, the blend tradition and modern design shopping mall; and Platinum Fashion Mall, a fashion and local food centre for medium economy class. Beside Wat Pho and Wat Arun, there are some temples that could be included in a toru package for the protected heritage culture destination.
There are Wat Phra Kaew, Wat Traimit, Wat Mahabut, Wat Suthat, The Grand Palace, and many others (thaiwebsites.com, 2020).
Those destinations will be very interesting for Indonesian millenials because their internal motivations of visiting Bangkok are getting knowledge and culture, friendship, social status, sightseeing, and experience. Meanwhile, theirexternal motivations are knowing and enjoying the local value, destination features, historical value, cultural value and outdoor attraction.
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